PlotS presents users with a range of eight graph types
to select from:
Certain graph like density, frequency and histogram require only
X-axis. The variable for Y-axis for the other remaining graph has to be
numeric variable. Users can interactively change the variable for the
axes.
The aesthetic choice serves as a valuable function that links a variable to a visual element like color, shape, or line type (dash, dotted, solid). This enables users to add additional variables or differentiate between variables. This functionality equips PlotS to effectively manage a wide range of data variables for analysis, setting it apart from other visualization tools.
To illustrate, we will use a hypothetical gene expression dataset (refer to Table 1) representing two rice cultivars (IR64 and N22) exposed to two types of treatments (t1 and t2), along with a control (c). Each condition has two replicates (R1, R2). Let’s create a scatter plot with aesthetic color mapped to treatment and Shape to replicate of the data. The resulting graphical representation is depicted in Figure 1.
Table 1. Expression data with two replicates of two rice cultivars under different treatment conditions. | |||
|---|---|---|---|
cultivar | treatment | replicate | fpkm |
IR64 | t1 | R1 | 20.90 |
IR64 | t1 | R2 | 17.75 |
IR64 | t2 | R1 | 5.90 |
IR64 | t2 | R2 | 3.39 |
IR64 | c | R1 | 7.60 |
IR64 | c | R2 | 6.60 |
N22 | t1 | R1 | 10.37 |
N22 | t1 | R2 | 11.93 |
N22 | t2 | R1 | 41.51 |
N22 | t2 | R2 | 33.64 |
N22 | c | R1 | 23.81 |
N22 | c | R2 | 28.01 |
Figure 1. Scatter plot with the chosen aesthetic elements - color and shape
PlotS offers various features for multivariate analysis in addition to the features provided under Aesthetic options. Visualization of the relationship of multiple variables in a data can be done in four ways:
Faceting
Secondary Y-axis
Side graph
Inset graph
Faceting generate sets of visual representations by partitioning data into smaller groups and showcasing identical graphs for each subgroup.
User has to select the Facet type. There are two types:
wrap
grid.
To exemplify the concept of faceting, we will utilize the provided Table 2. Although the data follows a format akin to Table 1, it contains a more comprehensive range of rows, providing a more detailed perspective.
Figure 2. displaying the wrap faceting
Figure 2. displaying the grid faceting
In certain cases dual Y-axis is necessary to display the relationship between variables. To add the secondary Y-axis, data must have two numeric variables (or columns) and users have to select any one graph listed under the “Add layer with secondary Y-axis”.
The Side graph functionality within PlotS offers an additional and valuable avenue for investigating the relationship between variables. It provide the flexibility to introduce graphs on either the right side (Y-graph) and/or the upper side (X-graph) of the primary graph. This feature is conveniently located beneath the main graph panel (shown below).
By default, the variables selected for the side graphs are aligned with those assigned to the X-axis and Y-axis of the main graph. However, users have the autonomy to opt for different variables when generating these side graphs.
It’s important to note that the Side graph feature is not compatible with the two-way ANOVA or when the secondary Y-axis is in use.
